Automated traffic management system and method

• US 6,161,097 A
• Filed: 06/04/1998
• Issued: 12/12/2000
• Est. Priority Date: 08/11/1997
• Status: Expired due to Fees

• Current Assignee: Administrator of The National Aeronautics and Space Administration
• Original Assignee: The United States of America As Represented By The Secretary of Agriculture
• Inventors: Gibson, James, Iverson, David L., Spirkovska, Liljana, Reisman, Ronald J., McDermott, William J., Glass, Brian J.
• Primary Examiner(s): Lintz, Paul R.
• Assistant Examiner(s): Hayes, John W.
• Application Number:
  US09/090,812
• Time in Patent Office: 922 Days
• Field of Search: 705/6, 345/23, 345/33, 345/36, 345/385, 345/456, 701/120, 701/117, 701/118, 701/119, 701/122
• US Class Current: 705/6
• CPC Class Codes: G06Q 10/025 Coordination of plural reservations, e.g. plural trip segments, transportation combined with accommodation
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G08G 5/0082 for monitoring traffic from a ground station radar or analogous systems specially adapted for traffic control G01S13/91
• CPC Class Codes: G08G 5/065 Navigation or guidance aids, e.g. for taxiing or rolling

Abstract

A data management system and method that enables acquisition, integration and management of real-time data generated at different rates, by multiple, heterogeneous incompatible data sources. The system achieves this functionality by using an expert system to fuse data from a variety of airline, airport operations, ramp control, and air traffic control tower sources, to establish and update reference data values for every aircraft surface operation. The system may be configured as a real-time airport surface traffic management system (TMS) that electronically interconnects air traffic control, airline data and airport operations data to facilitate information sharing and improve taxi queuing. In the TMS operational mode, empirical data shows substantial benefits in ramp operations for airlines, reducing departure taxi times by about one minute per aircraft in operational use, translating as $12 to $15 million per year savings to airlines at the Atlanta, Georgia airport. The data management system and method may also be used for scheduling the movement of multiple vehicles in other applications, such as, marine vessels in harbors and ports, trucks or railroad cars in ports or shipping yards, and railroad cars in switching yards. Finally, the data management system and method may be used for managing containers at a shipping dock, stock on a factory floor or in a warehouse, or as a training tool for improving situational awareness of FAA tower controllers, ramp and airport operators or commercial airline personnel in airfield surface operations.

Claims

1. A data management system comprising:

a server;

a plurality of input sources connected to said server via at least one communication link, for allowing users to input data into said server, said server processing said input data;

a plurality of destination sources connected to said server via said at least one communication link, for allowing users to selectively access said processed data;

said server including;

(a) an autonomous, expert executive subsystem responsible for the tasks comprising;

controlling other subsystems, starting and shutting down processes at scheduled times, monitoring system components for error and warning conditions, notifying system support personnel of detected system errors, and recovering from system failures;

(b) an information subsystem, capable of data fusion, responsible for the tasks comprising;

integrating other subsystems, communicating traffic raw input data to a prediction subsystem, providing inter-process management and control, processing input and output data to and from said integrated subsystems, processing data fed back from said prediction subsystem, and providing system housekeeping;

(c) an input data management subsystem for providing input data to said information subsystem;

(d) said prediction subsystem for integrating said traffic raw input data from said information subsystem, real-time monitoring of the actual airport or other facility performance, predicting the occurrence of selected events based on said traffic raw input data and actual said airport or other facility performance, and iteratively feeding said prediction data back to said information subsystem; and

(e) a client interface subsystem for providing user interface interactions to the system.

2. A data management system according to claim 1, further including a database that stores input data from said input management subsystem and predicted data from said prediction subsystem;

and

wherein said input data and said predicted data are processed by said information subsystem and are presented to said destination sources in the form of processed data.

3. A data management system according to claim 1, wherein said information subsystem includes a database that stores input data from said input management subsystem and predicted data from said prediction subsystem;

and

said input data and said predicted data are processed by said information subsystem and are presented to said destination sources in the form of processed data.

4. A method according to claim 1, wherein said prediction system periodically reorganizes arrays of departing and arriving flight objects, such that when a flight object position in an array changes, said prediction subsystem updates said arrays of departing and arriving flight objects to reflect the change.

5. A method according to claim 4 wherein said prediction subsystem uses landing direction and departure split to predict runway assignments.

6. A method according to claim 4, wherein said prediction subsystem revises and reassesses runway and facility assignments for elements in the array of departing and arriving flight objects each time there is a change in the position of said flight objects within said arrays.

7. A data management system according to claim 1, further including an archive file to which data from said database is transferred.

8. A data management system according to claim 1, wherein said autonomous, expert executive subsystem is further responsible for the task of facilitating subsystem debugging.

9. A data management system according to claim 1, wherein said autonomous, expert executive subsystem is further responsible for the task of providing remote access to the system.

10. A data management system according to claim 1, wherein said autonomous, expert executive subsystem is further responsible for the task of maintaining system statistics.

11. A data management system according to claim 1, wherein said autonomous, expert executive subsystem is further responsible for the task of managing user accounts.

12. A data management system according to claim 8, wherein said executive subsystem maintains a system configuration that includes system operation mode, airport configuration parameters, active subsystems identification, subsystem debugging information, and user authorizations.

13. A data management system according to claim 12, wherein said executive subsystem configuration maintains a record for each subsystem that includes an indication of whether each subsystem is active, idle, excluded, or in an error condition.

14. A method for operating a data management system, comprising the steps of:

(a) connecting a plurality of input sources to a server via at least one communication link, for allowing users to input data into said server, said server processing said input data;

(b) connecting a plurality of destination sources to said server via said at least one communication link, for allowing users to selectively access said processed input data;

(c) initiating an autonomous, expert executive subsystem responsible for performing the tasks comprising;

controlling other subsystems, starting and shutting down processes at scheduled times, monitoring system components for error and warning conditions, notifying system support personnel of detected system errors, and recovering from system failures;

(d) activating an information subsystem, capable of data fusion, responsible for performing the tasks comprising;

integrating other subsystems, communicating traffic raw input data to a prediction subsystem, providing inter-process management and control, processing input and output data to and from said integrated subsystems, processing data fed back from said prediction subsystem, and providing system housekeeping;

(e) activating an input data management subsystem for providing input data to said information subsystem;

(f) initializing said prediction subsystem for integrating said traffic raw input data from said information subsystem, for real-time monitoring of the actual airport or other facility performance, or predicting the occurrence of selected events based on said traffic raw input data and actual said airport or other facility performance, and iteratively feeding said prediction data back to said information subsystem; and

(g) initializing a client interface subsystem for providing user interactions to the system.

15. A method according to claim 14, further including the steps of:

storing input data from said input management subsystem and predicted data from said prediction subsystem in a database; and

processing said input data and said predicted data by said information subsystem and presenting processed data to said destination sources.

16. A method according to claim 14, wherein said autonomous, expert executive subsystem also facilitates subsystem debugging.

17. A method according to claim 14, wherein said autonomous, expert executive subsystem also provides remote access to system.

18. A method according to claim 14, wherein said autonomous, expert executive subsystem also maintains system statistics.

19. A method according to claim 14, wherein said autonomous, expert executive subsystem also manages user accounts.

20. A method according to claim 14, further including the step of having said prediction subsystem calculate an aircraft landing time estimate t(R) as follows:

##EQU4## where m=1, . . . , n are the n most recent flights past a terminal area airspace handoff point (H), and a runway outer marker (OM), and k_r is a site-defined constant equal to a typical difference in time from the outer marker to landing.

21. A method according to claim 20, wherein when an aircraft must go-around and attempt another landing, said prediction subsystem initially resets a landing time to a locally-defined constant km defined as follows

22. A method according to claim 21, wherein said prediction subsystem estimates the taxi duration for a given flight, as follows:

space="preserve" listing-type="equation">Δ

t.sub.m =(t.sub.t -t.sub.0) (3)

where t_t is the taxi termination time (gate arrival or takeoff and t₀ is the taxi start time (landing or pushback) for a given flight; and

wherein at any given time t, the estimated taxi time (calculated separately for arrivals and departures) is defined as follows;

##EQU5## where 1, . . . , p are most recently concluded taxiing flights values.

23. A method according to claim 22, wherein during periods of light activity the most recently-concluded taxi times may include some flights from hours before, and when taxi times occurred more than a predetermined period of time in the past, then a minimum taxi time constant k_t is used in calculating equation (4) as follows:

##EQU6## where t_t is the taxi termination time (gate arrival or takeoff) and t₀ is the taxi start time (landing or pushback) for a given flight; and

wherein at any given time t, the estimated taxi time (calculated separately for arrivals and departures) is defined as follows;

##EQU7## where 1, . . . , p are most recently concluded taxiing flights values.

24. A method according to claim 15, further including the step of transferring data from said database to an archive file.

25. A method according to claim 15, wherein said prediction subsystem initializes the following sequence of events by:

(a) calling a method of said executive subsystem to inform said executive subsystem that said prediction subsystem is in a "running" state;

(b) setting up gate-to-ramp mapping;

(c) creating aircraft objects having information about each type of aircraft; and

(d) getting an airport configuration and initializing landing direction and split.

26. A method according to claim 25, wherein said prediction subsystem processes a received input message by sequentially implementing the steps of:

(a) getting a call sign from said input message, and finding the corresponding flight object in said database;

(b) creating a new flight object, if said flight object is not found in said database;

(c) updating said flight with the new information just received via said input message;

(d) writing the updated flight object back to said database; and

(e) merging two related flight objects into single flight, if said input message is a stub flight message.

27. A method according to claim 16, wherein said executive subsystem maintains a system configuration that includes system operation mode, airport configuration parameters, active subsystems identification, subsystem debugging information, and user authorizations.

28. A data management system according to claim 27, wherein said executive subsystem configuration maintains a record for each subsystem that includes an indication of whether each subsystem is active, idle, excluded, or in an error condition.